Precision medicine and digital phenotyping: Digital medicine's way from more data to better health

Abstract

Precision medicine and digital phenotyping are two prominent data-based approaches within digital medicine. While precision medicine historically used primarily genetic data to find targeted treatment options, digital phenotyping relies on the usage of big data deriving from digital devices such as smartphones, wearables and other connected devices. This paper first focusses on the aspect of data type to explore differences and similarities between precision medicine and digital phenotyping. It outlines different ways of data collection and production and the consequences thereof. Second, it shows how these sorts of data influence dominant beliefs in the field: The field of precision medicine relying on the dominant understanding of ‘genetic determinism’ imported from genetics, digital phenotyping building on the logic of ‘data fundamentalism’. In the end, the analysis shows how digital data informs potentials as well as challenges of precision medicine and digital phenotyping: a better health care for (some) individuals connected with individualisation and responsibilisation for all, with a prognosed shift from reactive to preventive medicine. Additionally, data-based approaches might facilitate epistemological and ontological redirections for the whole field of medicine that will also affect knowledge production and a reassessment of the value of different types of knowledge (quantifiable vs. non-quantifiable) with all its consequences. Institutionally, it might lead to shifts in distribution of power to experts in big data related technologies, i.e. private companies.

Reinventing mental health care in youth through mobile approaches: Current status and future steps

“…Although, on one hand, digital phenotyping involves collecting massive amounts of individual data while creating a new category of health data and participation in risk assessment, on the other hand, existing ethical and regulatory frameworks for mental health care do not apply to digital phenotyping, creating the need to consider ethical, legal, and social implications ( Potier, 2020 ). Indeed, digital phenotyping collects data about location, physical activity, mood, speech patterns, typing speed, call activity, social media usage, passive sensing data of GPS location, call logs for behaviorally phenotyping loneliness, and digital biomarkers ( Baumgartner, 2021 ). However, the big data collected are still regarded as unclean and messy ( Baumgartner, 2021 ).…”

Digital phenotyping – Editorial

“…The third dimension assembles a series of perspectives to inspect closely what kind of conceptual allegiances and theoretical kinships are invoked through often pragmatically introduced digital phenotyping. Baumgartner asks for increased analytical attention to the use and analysis of data in precision medicine and digital phenotyping, so that the often implied ‘genetic determinism’ and ‘data fundamentalism’ are acknowledged (Baumgartner, 2021). Engelmann investigates the depth of ‘deep medicine’ and asks how the emergence of digital phenotyping has been coupled to the reinvigoration of the dream of total archives, risking the introduction of totalising and normative conceptions of health and disease (Engelmann, 2022).…”

Increasing the Value of Digital Phenotyping Through Reducing Missingness: A Retrospective Analysis

“…The potential of digital technologies for deepening understanding of the etiology, risk factors, and course of diverse health conditions is now well known 1 . Research quantifying the lived experience of those with mental health conditions through capturing real-time information from a myriad of sensors is one of the fast-growing applications of these methods 2 .…”